| Federated learning for predicting clinical outcomes in patients with COVID-19 I Dayan, HR Roth, A Zhong, A Harouni, A Gentili, AZ Abidin, A Liu, ... Nature medicine 27 (10), 1735-1743, 2021 | 528 | 2021 |
| Multiscale brain MRI super-resolution using deep 3D convolutional networks CH Pham, C Tor-Díez, H Meunier, N Bednarek, R Fablet, N Passat, ... Computerized Medical Imaging and Graphics 77, 101647, 2019 | 393 | 2019 |
| SegSRGAN: Super-resolution and segmentation using generative adversarial networks—Application to neonatal brain MRI Q Delannoy, CH Pham, C Cazorla, C Tor-Díez, G Dollé, H Meunier, ... Computers in Biology and Medicine 120, 103755, 2020 | 78 | 2020 |
| Rapid artificial intelligence solutions in a pandemic—The COVID-19-20 Lung CT Lesion Segmentation Challenge HR Roth, Z Xu, C Tor-Díez, RS Jacob, J Zember, J Molto, W Li, S Xu, ... Medical image analysis 82, 102605, 2022 | 64 | 2022 |
| Federated Learning used for predicting outcomes in SARS-COV-2 patients M Flores, I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, ... Research Square, 2021 | 54 | 2021 |
| Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study AR Porras, K Rosenbaum, C Tor-Diez, M Summar, MG Linguraru The Lancet Digital Health 3 (10), e635-e643, 2021 | 53 | 2021 |
| An iterative multi-atlas patch-based approach for cortex segmentation from neonatal MRI C Tor-Díez, N Passat, I Bloch, S Faisan, N Bednarek, F Rousseau Computerized Medical Imaging and Graphics 70, 73-82, 2018 | 17 | 2018 |
| Unsupervised MRI homogenization: application to pediatric anterior visual pathway segmentation C Tor-Diez, AR Porras, RJ Packer, RA Avery, MG Linguraru Machine Learning in Medical Imaging: 11th International Workshop, MLMI 2020 …, 2020 | 16 | 2020 |
| Simultaneous super-resolution and segmentation using a generative adversarial network: Application to neonatal brain MRI CH Pham, C Tor-Díez, H Meunier, N Bednarek, R Fablet, N Passat, ... | 13 | 2019 |
| Facial analysis technology for the detection of Down syndrome in the Democratic Republic of the Congo AR Porras, MS Bramble, KMB Amoti, C Dakande, H Manya, N Vashist, ... European journal of medical genetics 64 (9), 104267, 2021 | 9 | 2021 |
| Evaluation of cortical segmentation pipelines on clinical neonatal MRI data C Tor-Díez, CH Pham, H Meunier, S Faisan, I Bloch, N Bednarek, ... | 3 | 2019 |
| Federated learning for predicting clinical outcomes in covid-19 patients I Dayan, H Roth, A Zhong, A Harouni, A Gentili, A Abidin, A Liu, AB Costa, ... Nature Medicine, 2021 | 1 | 2021 |
| SegSRGAN: A software solution for super-resolution and segmentation using generative adversarial networks–Application to neonatal brain MRI Q Delannoy, CH Pham, C Cazorla, C Tor-Díez, G Dollé, H Meunier, ... | 1 | 2019 |
| DIPG-48. MRI volumetric and machine learning based analyses predict survival outcome in pediatric diffuse midline glioma ER Bonner, X Liu, C Tor-Diez, M Kambhampati, A Eze, RJ Packer, ... Neuro-Oncology 24 (Suppl 1), i29, 2022 | | 2022 |
| A machine learning-based screening tool for genetic syndromes in children–Authors' reply AR Porras, K Rosenbaum, C Tor-Diez, M Summar, MG Linguraru The Lancet Digital Health 4 (5), e296, 2022 | | 2022 |
| Réseaux antagonistes génératifs pour la reconstruction super-résolution et la segmentation en IRM Q Delannoy, CH Pham, C Cazorla, C Tor-Díez, G Dollé, H Meunier, ... Extraction et Gestion des Connaissances-Atelier Apprentissage Profond …, 2020 | | 2020 |
| Automatic segmentation of the cortical surface in neonatal brain MRI C Tor-Díez Ecole nationale supérieure Mines-Télécom Atlantique, 2019 | | 2019 |
| Super-résolution et segmentation simultanées d’IRM cérébrales néonatales par réseaux antagonistes génératifs CH Pham, C Tor-Díez, H Meunier, N Bednarek, R Fablet, N Passat, ... Congrès National d’Imagerie du Vivant (CNIV), 2019 | | 2019 |
| Multilabel, multiscale topological transformation for cerebral MRI segmentation post-processing C Tor-Díez, S Faisan, L Mazo, N Bednarek, H Meunier, I Bloch, N Passat, ... Mathematical Morphology and Its Applications to Signal and Image Processing …, 2019 | | 2019 |
| Une approche par patchs, multi-atlas, itérative pour la segmentation du cortex cérébral en IRM néonatale C Tor-Díez, N Passat, I Bloch, S Faisan, N Bednarek, F Rousseau Congrès Reconnaissance des Formes, Image, Apprentissage et Perception (RFIAP), 2018 | | 2018 |
